Welcome & Introduction

RAdelaide 2025

Author
Affiliation

Dr Stevie Pederson

Black Ochre Data Labs
Telethon Kids Institute

Published

July 8, 2025




http://blackochrelabs.au/RAdelaide25

Introduction

Who Am I?

Stephen (Stevie) Pederson (They/Them)

  • Adelaide, Kaurna Country, SA
  • Bioinformatician, Black Ochre Data Labs, Telethon Kids Institute (2022-)

. . .

  • Bioinformatician, Dame Roma Mitchell Cancer Research Laboratories (2020-2022)
  • Co-ordinator, UofA Bioinformatics Hub (2014-2020)
  • Best week ever: NAIDOC week, NB Awareness Week + R coding

Who Am I?

Stephen (Stevie) Pederson (They/Them)

  • R User for ~20 years \(\implies\) learnt when R was difficult!
  • Senior Author of 7 Bioconductor Packages
    • ngsReports, extraChIPs, motifTestR, transmogR
    • strandCheckR, sSNAPPY, tadar
  • Currently Co-Chair of Bioconductor Community Advisory Board

. . .

Made countless typos, horrible decisions and catastrophic errors

. . .

I crash R at least once a week…

Today’s Tutors

  • Dr Jimmy Breen & Dr Alastair Ludington (Black Ochre Data Labs)
  • Dr John Salamon & Dr Simon Lee (SAGC)

Housekeeping

  • Toilets are back near the lifts
  • Catering will be downstairs in the foyer

Thanks to everyone for sending your information through regarding dietary needs and existing knowledge

Homepage and Material

  • The workshop homepage is http://blackochrelabs.au/RAdelaide24
    • Data and course material available here
    • Will stay live in perpetuity
  • Links to notes available
    • Slides are directly re-formatted as a simple webpage
    • Slides are visible by clicking the RevealJS link below the TOC
  • Group communication can be done through https://bioinformaticshubsa.slack.com/
    • Join the #radelaide24 channel

Course Aims

  • Provide a deep understanding of how to work with data in R
    • Importing Data
    • Visualising Data
    • Understanding Data
  • Enable use of modern analytic approaches
    \(\implies\) reproducible research
  • Not just how \(\implies\) a deep understanding of underlying structures
  • The more code you type the more you learn

References

Chambers, John M. 1977. Computational Methods for Data Analysis. New York: Wiley.
———. 2020. “S, r, and Data Science.” Proc. ACM Program. Lang. 4 (HOPL): 1–17.